Pivoted matrix factorization techniques, and QR pivoting in particular, have become a popular choice for sensor placement [1]}, [2]} and feature selection in reduced-order modeling [3]}, [4]}, where the method is often referred to as the Discrete Empirical Interpolation Method (DEIM).
This approach dates back to P. Businger and G. H. Golub's seminal work [5]}, which introduced Householder-pivoted QR factorization for the purpose of feature selection in least squares fitting problems.
The approach is also closely related to orthogonal matching pursuit [6]} and simultaneous orthogonal matching pursuit [7]}, which are widely used sparse approximation algorithms.
